IT modernization remains a key pillar of CIOs’ strategic agendas, and even CEOs are coming around to the value that addressing legacy systems has in fueling transformation and innovation.
Yet a solid majority of application and infrastructure modernization projects are failing to meet expectations, with many IT leaders having to cut IT corners to divert money for AI, in addition to all the traditional problems that plague them.
Sixty-one percent of organizations have had to pause, delay, scale back, or fully abandon IT modernization initiatives in the past 24 months, according to a recent survey from managed services provider Ensono.
Major IT projects fail for a variety of reasons, including poor project management and a lack of clear metrics, but tight budgets and cost overruns create tangible impediments. More than seven in 10 respondents to Ensono’s survey say their modernization initiatives have exceeded the original budgets, with 27% exceeding budgets by 51% or more.
The failure rate is often due to a combination of factors, but IT budget diversion to AI projects is a major challenge for IT leaders, says Brian Klingbeil, chief strategy officer at Ensono.
“People are redeploying spend toward AI projects,” he says. “There’s a lot of pressure to keep up with everyone else.”
Reallocated budgets
Many organizations are stuck in long-term IT modernization traps, such as scope creep, while facing declining budgets for traditional IT upkeep due to AI.
“In what I see, scope creep contributes the most, and it is a discovery problem more than a governance one, because the organization learns what the legacy estate actually does at the moment it starts to move it,” says Michele Grant, executive global director at Cognizant, of IT modernization delays and failures.
“But AI budgets are a real competitor for the same money, and over the past two years I have watched modernization funding reallocated toward AI initiatives that promise a faster visible return,” she says.A recent report from digital adoption platform provider WalkMe found that, while digital transformation budgets grew from an average of $39.4 million to $54.2 million in a single year, most of that spending went to AI-related projects, says KJ Kusch, global field CTO there.
“I wouldn’t call it scope creep,” she adds. “It was a deliberate move.”
Kusch also sees adoption problems contributing to poor IT modernization outcomes when newer IT systems are too complicated for employees to use. “Users experience too much friction, so they go back to the ways they worked before,” she says.
The irony, Ensono’s Klingbeil says, is that AI can help accelerate IT modernization projects by performing tasks such as code discovery and cleaning up legacy code. Most organizations haven’t tried it yet, but using AI tools can significantly cut the costs and timelines of IT modernization, he adds.
The irony, Ensono’s Klingbeil says, is that AI can help accelerate IT modernization projects by performing tasks such as code discovery and cleaning up legacy code. Most organizations haven’t tried it yet, but using AI tools can significantly cut the costs and timelines for IT modernization, he adds.
“Two years ago, if you had a legacy platform you weren’t happy with, for whatever reason, choice A was to invest $150 million and five years of your life and maybe get lucky and pull it off,” he says. “Choice B was suck it up and live with it, and there was no choice C.”
The price of misalignment
Another factor that can sink an IT modernization initiative relates to organizational outcome and cost misalignment, Cognizant’s Grant says.
“Modernization is approved as a technology program and then asked to carry a business outcome that requires process and organizational change, and the cost of that change was never inside the original number,” she says.
It doesn’t surprise Grant that 61% of organizations in the survey had to pause, scale back, or scrap IT modernization programs. A pause is sometimes the right choice, she says.
“When the business case was written against an operating model that has since changed, continuing to spend against that case is the more expensive choice,” she explains. “What I would look at in that 61% is not the pausing. It is that the organizations I see pause without naming the condition that would let them resume, and a program that stops with no restart condition turns into spend that nobody owns.”
A good way to control IT modernization costs is to fund the program in phases tied to named outcomes and give one executive the authority to stop the work, Grant recommends.
“A program that can only be slowed by consensus is never slowed; it is extended,” she adds.
AI needs modernization
Even as AI initiatives take spending away from modernization efforts, the two transformation priorities are closely linked.
Stu Bradley, senior VP of risk, fraud, and compliance solutions at analytics and data management vendor SAS, emphasizes that IT modernization leads to better AI outcomes.
“Seeing AI and modernization as competing budget lines is a bit of a trap,” he says. “In reality, AI and modernization are increasingly two sides of the same coin. Many organizations are discovering that the AI capabilities they want depend on investments in data, integration, infrastructure, and governance that they’ve deferred for years.”
Recent SAS research found that only 17.5% of organizations have data infrastructure fully optimized to support agentic AI readiness, he notes.
“Rather than argue over competing budgets, leaders need to understand which modernization investments are prerequisites for the AI outcomes they’re aiming to achieve and fund them as part of the same business case,” he adds.
It also doesn’t surprise Bradley that most IT modernization pause or fail. “When you consider the pace of technology and how quickly priorities are shifting around AI, I’d frankly be more surprised if organizations weren’t regularly reevaluating their transformation projects,” he says.
But pauses or delays in project aren’t always failures, he notes. The priority during a pause should be identifying and addressing the issues that stalled the project, he recommends.
“CIOs should be willing to reevaluate initiatives rather than let momentum blindly drive continued investment,” he says. “Where organizations get into trouble is simply bumping the project into the next budget cycle hoping that somehow conditions will be different.”
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